This disclosure generally relates to content distribution of online systems, and in particular to optimizing for long attribution window (e.g., 14 days) conversion with an additive decomposition model.
Content providers produce content to target their content towards certain audiences within online systems. With the advent of online systems such as social networking systems, content providers have increasingly relied on the online systems to create effective sponsored content within the online system to greatly increase engagement among users of the online systems. There is a cost associated with sending content to a user, and the content provider would like to optimize how content is created and delivered to the user. If a content provider sends the content to a user that is not interested in the content, the content provider wastes resources. If the content provider does not send the content to a user when the user is receptive to the content, the content provider does not take advantage of the user's interest.
To enhance content delivery within an online system, the online system for a content provider may predict the probability of a predefined action happening after a campaign is launched from the content provider. However, the online system may have to wait until enough data is collected to improve delivery of content to users. For example, the online system can predict the probability of a predefined action happening given an impression/click, or can predict the conversion rate. However, conversion events can span over a wide range of content delivery spectrum, e.g., from clicking a link, viewing a home page of a content item, to adding to a shopping cart and purchasing. Existing solutions for modeling clicks and conversions predict the conversion rate for conversion events that happen within 1-day post click, i.e., a 1-day attribution window. Although a 1-day attribution window may be reasonable for conversion events such as viewing a product home page right after a click, other conversion events such as adding to a shopping cart or purchasing may happen days or even weeks after a click. For example, for content providers in the travel business, it usually takes a much longer time for a user to decide whether to buy airline tickets after the user clicks an online offering from a content provider. The gap between what existing solutions offer and what content providers really care about can have a negative impact on the content providers' experience with the online system.